OFDM is becoming increasingly popular in design of high data rate communication and broadcasting systems. OFDM transmitting and receiving systems and methods are well known for audio, video and/or data communication. In general, OFDM is a spread spectrum technique that distributes data over a large number of carriers that may be spaced apart at various frequencies. More specifically, OFDM converts data input in series along the time axis into data in parallel, performs an Inverse Fast Fourier Transform (IFFT) with respect to the data in parallel, then converts the inverse-transformed data in parallel into data in series, and transmits the data in series to an OFDM receiver after translating to radio frequencies. The OFDM receiver down converts the input signal in frequency and generates a digital signal. In this case, the digital signal is transformed by a Fast Fourier Transform (FFT) so that the digital signal is restored to an original signal.
The main processing of the received OFDM signal is well known to those skilled in the art. Briefly, the OFDM receiver carries out the following operations: a low-frequency translation of the OFDM received, an analog to digital conversion followed by a serial to parallel conversion and a Discrete Fourier Transform (DFT) (being typically carried out by FFT). The DFT (by transforming the signals from the time to the frequency domain) carries out the demodulation of the OFDM signal thus allowing obtaining the digital signals carrying the symbols relative to each of the sub carriers on several outputs.
Thus, the DFT provides discrete frequency domain representation of a discrete time signal. The computation of the finite number of frequency domain samples is very efficient compared to the conventional continuous time Fourier Transform. Generally, the DFT is computationally intensive for large values of N involving direct computation complexity of O(N2) for the N point DFT, wherein O is an asymptotic upper bound function for large values of N. The DFT may be computed more efficiently by using FFT approach. One popular FFT approach known as radix 2 FFT has a complexity of O(N log 2N), in which the length of the FFT, N, is a power of 2.
The modern high data rate OFDM based wireless communication systems put an increasing demand on the speed requirement of FFT. The Application Specific Integrated Circuits (ASICs) device to implement OFDM must have a very high speed FFT processor, while keeping the die size and power consumption low.
Conventional FFT hardware architectures include trade-offs among complexity, power consumption, die size, and other such parameters. However, these architectures do not have the scalability to meet the high speed demands of the OFDM processor for the emerging high data rate wireless technologies, such as Ultra-Wideband (UWB) or 802.11n wireless standard that can support data rate of about 480 mbps and beyond, thereby demanding higher speed FFT processors.